The Conductance Ratio Method for Off-Design Heat Exchanger Modeling and its Impact on an sCO2 Recompression Cycle
Bibliographic record
Abstract
This paper presents a method to evaluate the off-design performance of a heat exchanger without specifying detailed heat exchanger geometry. Presently, off-design heat exchanger performance evaluation is often done by assuming one of the terms in a lumped volume approach is constant (such as UA, temperature difference, ε etc.) or by producing a draft heat exchanger geometry to evaluate the local heat transfer coefficients in off-design operation. As opposed to these approaches, the method presented in this paper manages to accurately predict off-design heat exchanger performance with very limited information. The method relies on a single parameter beyond the design operating conditions, namely the conductance ratio which is the product of heat transfer coefficient and area on both sides of the heat exchanger. The method is particularly powerful as it allows for the exploration of different off-design scenarios for a given on-design operating point. The paper presents a theoretical introduction of the method along with a validation using data provided by BMPC and Alfa Laval for different types of heat exchangers and working fluids, including supercritical CO2. The method is then used to model the off-design performance of a simple recuperated sCO2 cycle, showing its ability to capture the off-design performance of a heat exchanger without specifying its detailed geometry and the impact of conductance ratio on off-design cycle performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".